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Leg dominance reflects the preferential use of one leg over another and is typically attributed to asymmetries in the neural circuitry. Detecting leg dominance effects on motor behavior, particularly during balancing exercises, has proven difficult. The current study applied a principal component analysis (PCA) on kinematic data, to assess bilateral asymmetry on the coordinative structure (hypothesis H1) or on the control characteristics of specific movement components (hypothesis H2). Marker-based motion tracking was performed on 26 healthy adults (aged 25.3 ± 4.1 years), who stood unipedally on a multiaxial unstable board, in a randomized order, on their dominant and non-dominant leg. Leg dominance was defined as the kicking leg. PCA was performed to determine patterns of correlated segment movements ("principal movements" PMks). The control of each PMk was characterized by assessing its acceleration (second-time derivative). Results were inconclusive regarding a leg-dominance effect on the coordinative structure of balancing movements (H1 inconclusive); however, different control (p = 0.005) was observed in PM3, representing a diagonal plane movement component (H2 was supported). These findings supported that leg dominance effects should be considered when assessing or training lower-limb neuromuscular control and suggest that specific attention should be given to diagonal plane movements.

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The current project investigated the dynamics of postural movements and muscle activity during balancing with feet-together and feet-apart positions on different support surfaces (firm surface (FS), modified- and conventional balance boards). We hypothesized that movement complexity and muscle activation would increase with increased balance-task difficulty, and that differences in the composition and control of postural movements between bipedal wide- and narrow-based balancing would be observed in all surface conditions. We applied a principal component analysis (PCA) to decompose postural movement trajectories of 26 active-young adults into sets of movement components (principal movements; PMs). Three PCA-based variables were calculated for each PM: the cumulative relative variance as a measure of movement complexity; the relative explained variance as a measure of the composition of postural movements; and the PM-acceleration as a measure for the control of the movement components. The main results revealed that both movement complexity and muscle activity increased with increased balance-task difficulty, of which altering support surfaces yielded more and greater effects than changing feet positions. Only on the FS, different movement structures were observed between narrowed- and wide-based standing (p ≤ 0.016); whereas different control of PMs was observed on all surfaces (p < 0.05). Standing on the stable surface illustrated opposite control behaviors compared to balancing on both multiaxial-unstable surfaces. In summary, on stable surface, changing the feet position affected inter-segment coordination. On unstable surfaces, the postural control system appeared to maintain inter-segment coordination characteristics, while the adaptation was confined to the sensorimotor integration processes.

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Leg dominance has been reported as one potential risk factor for lower-limb injuries in recreational downhill skiers. The current study proposed and tested two possible mechanisms for a leg dominance effect on skiing injuries-imbalance of the knee muscle strength and bilateral asymmetry in sensorimotor control. We hypothesized that the knee muscle strength (Hypothesis 1; H1) or postural control (Hypothesis 2; H2) would be affected by leg dominance. Fifteen well-experienced recreational downhill skiers (aged 24.3 ± 3.2 years) participated in this study. Isometric knee flexor/extensor muscle strength was tested using a dynamometer. Postural control was explored by using a kinematic principal component analysis (PCA) to determine the coordination structure and control of three-dimensional unipedal balancing movements while wearing ski equipment on firm and soft standing surfaces. Only H2 was supported when balancing on the firm surface, revealing that when shifting body weight over the nondominant leg, skiers significantly changed the coordination structure (p < 0.006) and the control (p < 0.004) of the lifted-leg movements. Based on the current findings, bilateral asymmetry in sensorimotor control rather than asymmetry in strength seems a more likely mechanism for the previously reported effect of leg dominance on lower-limb injury risk in recreational downhill skiers.

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Motion analysis is used to study the functionality or dysfunctionality of the neuromuscular system, as human movements are the direct outcome of neuromuscular control. However, motion analysis often relies on measures that quantify simplified aspects of a motion, such as specific joint angles, despite the well-known complexity of segment interactions. In contrast, analyzing whole-body movement patterns may offer a new understanding of movement coordination and movement performance. Clinical research and sports technique evaluations suggest that principal component analysis (PCA) provides novel and valuable insights into control aspects of the neuromuscular system and how they relate to coordinative patterns. However, the implementation of PCA computations are time consuming, and require mathematical knowledge and programming skills, drastically limiting its application in current research. Therefore, the aim of this study is to present the Matlab software tool "PManalyzer" to facilitate and encourage the application of state-of-the-art PCA concepts in human movement science. The generalized PCA concepts implemented in the PManalyzer allow users to apply a variety of marker set independent PCA-variables on any kinematic data and to visualize the results with customizable plots. In addition, the extracted movement patterns can be explored with video options that may help testing hypotheses related to the interplay of segments. Furthermore, the software can be easily modified and adapted to any specific application.

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Postural control research suggests a non-linear, n-shaped relationship between dual-tasking and postural stability. Nevertheless, the extent of this relationship remains unclear. Since kinematic principal component analysis has offered novel approaches to study the control of movement components (PM) and n-shapes have been found in measures of sway irregularity, we hypothesized (H1) that the irregularity of PMs and their respective control, and the control tightness will display the n-shape. Furthermore, according to the minimal intervention principle (H2) different PMs should be affected differently. Finally, (H3) we expected stronger dual-tasking effects in the older population, due to limited cognitive resources. We measured the kinematics of forty-one healthy volunteers (23 aged 26 ± 3; 18 aged 59 ± 4) performing 80 s tandem stances in five conditions (single-task and auditory n-back task; n = 1-4), and computed sample entropies on PM time-series and two novel measures of control tightness. In the PM most critical for stability, the control tightness decreased steadily, and in contrast to H3, decreased further for the younger group. Nevertheless, we found n-shapes in most variables with differing magnitudes, supporting H1 and H2. These results suggest that the control tightness might deteriorate steadily with increased cognitive load in critical movements despite the otherwise eminent n-shaped relationship.

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Sample entropy (SaEn) applied on center-of-pressure (COP) data provides a measure for the regularity of human postural control. Two mechanisms could contribute to altered COP regularity: first, an altered temporal structure (temporal regularity) of postural movements (H1); or second, altered coordination between segment movements (coordinative complexity; H2). The current study used rapid, voluntary head-shaking to perturb the postural control system, thus producing changes in COP regularity, to then assess the two hypotheses. Sixteen healthy participants (age 26.5 ± 3.5; seven females), whose postural movements were tracked via 39 reflective markers, performed trials in which they first stood quietly on a force plate for 30 s, then shook their head for 10 s, finally stood quietly for another 90 s. A principal component analysis (PCA) performed on the kinematic data extracted the main postural movement components. Temporal regularity was determined by calculating SaEn on the time series of these movement components. Coordinative complexity was determined by assessing the relative explained variance of the first five components. H1 was supported, but H2 was not. These results suggest that moderate perturbations of the postural control system produce altered temporal structures of the main postural movement components, but do not necessarily change the coordinative structure of intersegment movements.

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Human movements, recorded through kinematic data, can be described by means of principal component analysis (PCA) through a small set of variables representing correlated segment movements. The PC-eigenvectors then form a basis in the associated vector space of postural changes. Similar to 3D movements, the kinematics in this posture space can be quantified through 'principal' positions (PPs), velocities (PVs) and accelerations (PAs). The PAs represent a novel set of variables characterizing neuro-muscular control. The aim of the current technical note was to (i) compare the variance explained by PAs with the variance explained by PPs; (ii) clarify the relationship between PAs and segment accelerations; and (iii) compare variability of the first principal acceleration (PA1) with the local dynamic stability (largest Lyapunov exponent, LyE) of the first principal position (PP1). A PCA was applied on 3D upper-body positions collected by an Xsens inertial sensor system as nineteen volunteers performed a bimanual repetitive tapping task. The main finding revealed that the PP-explained variance considerably differed from the PA-explained variance, indicating that the latter should be considered when reducing the dimensionality in postural movement analysis through a PCA. Further, the current study formally established that the acceleration curves obtained from differentiating segment positions and from linear combinations of PAs are identical. Finally, a strong correlation, r(17) = 0.92, p < 0.001, was observed between the cycle-to-cycle variability in PA1 and the LyE calculated for PP1, supporting the notion that PA variability and LyE share some of the information they provide about movement control.

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In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

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BACKGROUND: Movement variability in sustained repetitive tasks is an important factor in the context of work-related musculoskeletal disorders. While a popular hypothesis suggests that movement variability can prevent overuse injuries, pain evolving during task execution may also cause variability. The aim of the current study was to investigate, first, differences in movement behavior between volunteers with and without work-related pain and, second, the influence of emerging pain on movement variability. METHODS: Upper-body 3D kinematics were collected as 22 subjects with musculoskeletal disorders and 19 healthy volunteers performed a bimanual repetitive tapping task with a self-chosen and a given rhythm. Three subgroups were formed within the patient group according to the level of pain the participants experienced during the task. Principal component analysis was applied to 30 joint angle coordinates to characterize in a combined analysis the movement variability associated with reconfigurations of the volunteers' postures and the cycle-to-cycle variability that occurred during the execution of the task. FINDINGS: Patients with no task-related pain showed lower cycle-to-cycle variability compared to healthy controls. Findings also indicated an increase in movement variability as pain emerged, manifesting both as frequent postural changes and large cycle-to-cycle variability. INTERPRETATION: The findings suggested a relationship between work-related musculoskeletal disorders and movement variability but further investigation is needed on this issue. Additionally, the findings provided clear evidence that pain increased motor variability. Postural reconfigurations and cycle-to-cycle variability should be considered jointly when investigating movement variability and musculoskeletal disorders.

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The main purposes of the current study were to examine bilateral asymmetry in postural control during single-leg standing between the dominant and non-dominant legs using a novel analysis approach based on principal component analysis (PCA). It was hypothesized that the asymmetry might manifest as differences in the coordinative structure (control strategies), or as differences in the frequency or regularity of corrective interventions of the motor control system. The static and dynamic leg dominance of 26 active young adults (14 males and 12 females) was determined from their preferred leg for dynamic and for static tasks. Then postural movements during one-leg standing were recorded with a standard marker-based motion capture system and analyzed by a PCA. The coordinative structure of postural movements was quantified using the relative variance of the principal movement components (PMs). Then the PMs were differentiated to obtain postural accelerations, from which two variables characterizing the activity (frequency and regularity) of the postural control system were derived. There were no differences in the coordinative structure, neither for dynamic nor for static leg preference. However, both variables characterizing asymmetries in the postural accelerations showed significant differences in specific PMs. Dynamic leg dominance yielded more and larger effects than static leg dominance. In the opinion of the authors, the PM-specificity of limb dominance agrees with principles of movement control derived from optimal feedback control theory. In summary, the current study suggests that leg dominance should be considered in clinical testing; different effects in different movement components should be expected; and one-leg standing should be seen as a dynamic, rather than as a static task.

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Optimal feedback control theory suggests that control of movement is focused on movement dimensions that are important for the task's success. The current study tested the hypotheses that age effects would emerge in the control of only specific movement components and that these components would be linked to the task relevance. Fifty healthy volunteers, 25 young and 25 older adults, performed a 80s-tandem stance while their postural movements were recorded using a standard motion capture system. The postural movements were decomposed by a principal component analysis into one-dimensional movement components, PMk, whose control was assessed through two variables, Nk and σk, which characterized the tightness and the regularity of the neuro-muscular control, respectively. The older volunteers showed less tight and more irregular control in PM2 (N2: -9.2%, p = 0.007; σ2: +14.3.0%, p = 0.017) but tighter control in PM8 and PM9 (N8: +4.7%, p = 0.020; N9: +2.5%, p = 0.043; σ9: -8.8%, p = 0.025). These results suggest that aging effects alter the postural control system not as a whole, but emerge in specific, task relevant components. The findings of the current study thus support the hypothesis that the minimal intervention principle, as described in the context of optimal feedback control (OFC), may be relevant when assessing aging effects on postural control.

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Sample entropy (SaEn), calculated for center of pressure (COP) trajectories, is often distinct for compromised postural control, e.g., in Parkinson, stroke, or concussion patients, but the interpretation of COP-SaEn remains subject to debate. The purpose of this paper is to test the hypotheses that COP-SaEn is related (Hypothesis 1; H1) to the complexity of the postural movement structures, i.e., to the utilization and coordination of the mechanical degrees of freedom; or (Hypothesis 2; H2) to the irregularity of the individual postural movement strategies, i.e., to the neuromuscular control of these movements. Twenty-one healthy volunteers (age 26.4 ± 2.4; 10 females), equipped with 27 reflective markers, stood on a force plate and performed 2-min quiet stances. Principal movement strategies (PMs) were obtained from a principal component analysis (PCA) of the kinematic data. Then SaEn was calculated for the COP and PM time-series. H1 was tested by correlating COP-SaEn to the relative contribution of the PMs to the subject specific overall movement and H2 by correlating COP-SaEn and PM-SaEn. Both hypotheses were supported. This suggests that in a healthy population the COP-SaEn is linked to the complexity of the coordinative structure of postural movements, as well as to the irregularity of the neuromuscular control of specific movement components.